Very few industries share data. At some level, every industry measures results and tests products, offers and media.
Few companies cover an entire market segment vertically. Most sell only a specialised set of related products. The sellers of related products would do well to share information with one another.
Few industries, however, are willing to share customer data for the common good.
But there is a huge amount of common data that is now available. The rise of the ‘like’ economy has led to a huge surge in information. Thanks to social networking sites such as Facebook, YouTube, Twitter and internet gate-keepers such as Google, digital marketers are able to tap into a treasure trove of consumer affiliations. All the data about your brands being left by consumers as “digital exhaust” is out there for all to analyse.
Facebook controls the most “like” data, recording more than 80 billion per month at last check. But Twitter records more “talking” than anyone else (1.5 billion tweets per month); Amazon collects the most reviews (well over 6 million per month); and Google’s YouTube and Google Display Network have data on how a billion people prefer to spend their time.
The future of brand advertising, hinges on the effective monitoring of social behaviours, believes research agency Forrester. Such behaviours reveal long-term emotional drivers, as opposed to search behaviour, which reveals shorter-term, rational clues. A new research group within Facebook, is working on an emerging and powerful approach to artificial intelligence known as deep learning, which uses simulated networks of brain cells to process data. Applying this method to data shared on Facebook could allow for novel features and perhaps boost the company’s ad targeting.
As companies do a better job of capturing accurate transaction information, they build a valuable asset not only for themselves, but also for other marketers. Savvy marketers are looking for partners with whom they can trade their data. Data's value increases when it's shared, and you can make money by selling it.
Sharing data increases its value by reinforcing crucial relationships in the business ecosystem.
1. The data you receive in return adds valuable marketing perspective that you probably can't get on your own.
2. Sharing data helps transform your channel relationships from transactional into long-term partnerships, which can fend off price competition and open doors to other co-marketing activities.
Twitter, which went public recently, made $47m of its total $422m revenue from sales of its data over the past nine months, an increase of 36 per cent from the same period the year before.
EBay now enables advertisers to use the data about how visitors browse the site, what they buy, and more, which the company kept as proprietary until now, to target ads and increase return on investment. Even though personally identifiable information won’t be provided to advertisers, eBay visitors’ search and purchase data alone could be a goldmine to consumer product brands. Suddenly, brands have an exponentially greater ability to get the right ads in front of the right audiences. In other words, eBay (like Amazon before it) is monetizing its customer data by allowing advertisers to retarget the eBay audience. Ads must be purchased through eBay in order for brands to access this customer data, and eBay will handle its own ad buying as well as the ad buying for all of the third-party marketers accessing its data.
Forrester has dubbed this social, emotional data the ‘database of affinity.’ With all of this information comes the incredible power of accurate brand advertising, but actually wading through the dense and what now appears to be endless amounts of data will be the greatest challenge.
And Forrester says, surprisingly, that Google is better positioned to leverage this "database of affinity" than Facebook!!
So what does this mean for Marketers?
1. How are you monetising your data? Think about the value that it can add, not just the revenue? Remember "Data equity" is likely to become more powerful than even "Brand equity" in the years to come.
- How are you getting all this social data together into one platform for your brand teams to analyse?
- You don’t own this data & the Facebook’s & Linked In’s of the world own it. So how are you creating a Social CRM strategy that allows you to directly engage with customers & own that data. Important for brands to add in data capture forms into their promotions to help build out data they need for a Social CRM strategy. If you don't ask, you don't get and you don't own. That's the reality of social media marketing.
- And how are you linking social with the rest of your CRM efforts? Do you have a “one View” of CRM?
HeHere is an interesting article on Forrester’s definition of the “Database of affinity”
Transforming The Retail Banking Customer Service Experience By Speaking With One Bank Customer at A Time is not easy & most banks would hesitate to make any drastic innovations in this space.
And this is why Umpqua bank excited me. Their Seattle branch lobby hotline invites customers to reach out directly to Umpqua Bank president Ray Davis. I cannot imagine this in any service organisation? Would a leader take this chance? Is Customer experience so important for leaders today? Is it more important for some industries vs others? Financial institutions also suffer from an overall trust deficit amongst consumers, doesn't that mean they must try harder!
And yet,consumer trust in the top 50 global financial institutions remained negative in the third quarter of 2013, according to a benchmarking index from Thomson Reuters measuring brand sentiment in both social and news media channels.
Forrester Research recently asked senior bank executives whether they were meeting customer service needs better than competitors. Naturally, 60 percent said yes. Customers painted a different picture. Less than half (45 percent) believe that financial institutions are doing a good job of meeting their needs and only 10 percent said that the service was truly excellent
And yet, customer expectations have grown. Customers aren’t just comparing their banking experience to their other banking experiences. Now, they’re comparing it to their shopping experience at Apple, Amazon and any other company that has optimized not only the offer that is delivered but also the way that it is delivered. If you the see the numbers below, banking doesn't do well when compared with other industries
Customers are increasingly saying that the experience provided by my bank is going to drive my bank of choice -my primary bank.
India is in the process of granting licenses to new banks. Would one of these new banks build an institution around a "diffrentiated customer experience"? Banks will have to work hard to diffrentiate themselves. If customer complaints are a metric, then Indian banks have a lot of work to do!
And while only about one in five customers are taking their service issues to social media, according to the American Express 2012 Global Customer Service Barometer, among those customers 46 percent say they take to social media to vent frustration with a bad customer service experience. That’s free competitive research for you, if you care enough to listen to it.
Once you collect that data, and feed it into your CRM, the next step is to act quickly.
And it amazes me that banks are not transforming the way they do CRM. For years, companies have relied on their contact centres to deal with customer interactions, from statement information to requesting for a credit card. But contact centres need to evolve.They need to morph from being "transaction centres to becoming Relationship Hubs"
Driven by a shift in technology capabilities and consumer behaviour, leading companies can refocus contact centres from handling individual calls to building customer loyalty. But this needs a complete change in mindset. It also requires that banks powerfully leverage the data that they have to make 1to1 interactions happen at the Contact centre.These changes will morph contact centres into Relationship Hubs.
To do this banks have to think differently:
- Create a Customer experience roadmap. Don't let the practical limitations of existing processes , stop you in your tracks.
- Bring your centralised Analytics function to participate in building a Customer Relationship hub. Leverage the rich information insight to drive a "intelligence to interaction" strategy.
- Transform your Marketing function with the "To service is to Sell" philosophy by integrating Service based thinking with Event triggered marketing.
- Ask Marketing to work with the CIO to create a Technology backbone to this Customer experience strategy.
Do company boards get as involved in marketing as they need to? Can they afford not to? Are companies wasting Marketing money in their never ending quest for new customers? Shouldn’t the company’s board lead the journey towards “finding products for customers” (customer centricity) rather than limiting the company to only look at “finding customers for products” (product centricity)( comment from Don Peppers).
Gail J. McGovern, a professor of management practice at Harvard Business School, says that “Organizations take their cues from the top. When the board turns its attention to the company’s customers, the entire organization will become more market driven, more customer-centric, and more focused on generating organic growth”.
HP has transitioned their CMO, Marty Homlish, and fitted him into a new role of “Chief Customer Experience Officer”. This role will focus on driving more consistent and high-value interactions with customers across all business units.
All over the world, more customers are feeling discomfort about how companies treat them. They experience bad service, complex products & they are shocked by hidden costs. And yet Customer centricity as a theme is much talked about in the corporate world. So is Customer centricity more about lip service than reality. Do Companies talk about it but rarely put it in practise. Or are there some companies who genuinely are making an effort to be far more customer centric. Are some industries better at it, think Apple, Disney & others notoriously bad, think banks! Being Customer centric should be the means & not the end. After all eventually companies want to profit from engaged & satisfied customers.
And yet Customer centricity does deliver results. HBS professor Ranjay Gulati has deeply researched this issue. Customer-centric companies tracked by Gulati between 2001 and 2007 delivered shareholder returns of 150 percent while the S&P 500 delivered 14 percent. Gulati focuses on what he calls the “outside in” perspective. An outside-in perspective means that companies aim to creatively deliver something of value to customers, rather than focus simply on products and sales
What does Customer centricity mean to you? I would love to have your feedback. Here is what I feel:
- Being loyal to customers & not the other way around (customers needing to be loyal to the company). This needs companies to have a longer term view of customer lifetime value & not a short term view of immediate profit. It needs an internal senior level stakeholder who champions the customer cause (CMO?)
- Become more accessible to customers & respond faster to their needs. This needs companies to move from “insight to action”. To act faster, companies need to break silos within their organisation to be able to respond to customers.
- Use information to make every interaction relevant & use customer data to more powerfully personalise company’s interactions with the customer. The Big data world is only producing more such information for marketers to leverage. This amounts to a mass customisation strategy where the CIO & CMO need to work very closely together to make meaningful changes in the company’s operating environment. And most critically, to do this keeping the customers sensitivity to privacy as paramount!
Analytics and data are transforming companies around the world. Yet one of the great difficulties with analytics is that it can be difficult to explain and understand; it is widely held that analytics specialists don’t communicate well with decision makers, and vice-versa.
As a result, analytics adoption is still not easy within companies. Analysts, at one end, are busy learning more specialised & deeply technical methods of analysing data & at the same time they are finding it difficult to get theses stories “heard” within organisations. Influencing ultimate decision makers is similar to selling products or services to external customers. Analysts need to understand that when they present ideas to decision makers, it is their responsibility to sell – not the decision maker’s responsibility to buy
Stories are the best way to influence! But we don’t see them being used so often. Analytics doesn’t need you to solve only a technical problem but a “social” one. Analytics is sexy but for it to make an impact, it needs to be embedded into the fabric of the company. This calls for analysts to become more social & in fact better presenters & story tellers. They need to learn to demystify analytics & link it to practical ways for the business to make money! And analysts need to learn to link their work to “the last mile”. Analytics should not be expected to deliver a “Aha moment”, instead it should be a “factory approach to improved decisions”. So analytics is not just a planning tool as much as it is an Execution tool to improve the customer experience & business impact. Start with a decision in mind & work backwards, not with the data in mind & working forward
Compare the analytics industry with the world of journalism. One of the most deadline filled industries in the world is getting it right with what it calls precision journalism! Despite crazy deadlines, I am amazed at the powerful stories journalists write using data. I wish the analytics industry was half way as good!!
Here is an example from the New York times:
I can relate to the data above by filtering it to my exact demographic. Suddenly a dry topic like Jobless rates for the economy as a whole, becomes far more real & human to me.
The corporate world needs to learn from this & use data to tell stories better! Journalists are coping with the rising information flood by borrowing data visualization techniques from computer scientists, researchers and artists. Some newsrooms are already beginning to retool their staffs and systems to prepare for a future in which data becomes a medium
Analysts are often tempted to communicate how they did the analysis: “First we removed the outliers from the data, then we did a logarithmic transformation; that created high autocorrelation, so we created a one-year lag variable”—& the typical business user is already yawning! The audiences for analytical results don’t really care what process you followed; they only care about results and implications
Here is an example of a master storyteller. Hans Rosling, a Swedish professor, popularized this approach with his frequently viewed TED Talk that used visual analytics to show the changing population health relationships between developed and developing nations over time. Rosling has created a website called Gapminder (www.gapminder.org) that displays many of these types of interactive visual analytics
In early 2010, The New York Times was given access to Netflix’s normally private records of what areas rent which movies the most often. The Times created an engaging interactive database that let users browse the top 100-ranked rentals in 12 US metro areas, broken down to the postal code level. A colour-graded “heatmap” overlaid on each community enabled users to quickly scan and see where a particular title was most popular.
Analytics needs journalists within their community to help make the data human!
Look at the Netflix inforgraphic here:
CMO’s are going through turbulent times. According to a recent Accenture report, more than 70% of marketers in B2C, B2B2C and significant-growth companies feel this way. Marketers in APAC feel even stronger (85%).
Traditional skills that CMO's have are important but a new breed of Technology skills are gaining currency!
Till recently, when we spoke about Data based marketing, it always seemed to be a niche with most marketers doing it as an “add on” to the big marketing jobs consisting of Advertising & promotions. Data based marketers seemed to be these very passionate people with comparatively little impact in the bigger scheme of things. Also data seemed to be more important in some industries, banking & telecom as against others like FMCG! But it is interesting how this world is changing! And the changes are not only driving a larger “data orientation” amongst marketers, it is also driving a fundamental change on how Marketing can contribute to Revenue generation. I have written a short piece on this here : Marketing turns Left
Nowhere is this more evident than in the Online space. Google is an amazing example. In 2009, Google ran 12,000 experiments. Their chief economist, Hal Varian, has praised controlled experimentation as “the gold standard” for understanding cause-and-effect. But it’s not just the number of experiments they run that is impressive. Out of those 12,000 experiments that Google ran, only about 10% of them resulted in the tested change being adopted into their business. So 90% of the experiments they tried, didn’t “succeed.” This reveals Google’s true cultural differentiation — they’re willing to try a large number of ideas and be okay with failure. Surprising that in the physical world, you have far fewer examples of this with Capital One being a huge exception. Capital One is a bank built on intelligent experimentation & learning from experience.
In contrast, embracing continuous experimentation enables what David Armano has called unconventional marketing. Test new ideas on a small scale, measure and improve them in a succession of rapid iterations, learn from experience, and then create a “bigger bang” with the winner ideas.
So what does all this mean to the CMO. Rapid change from the earlier ways of marketing, for sure. How does the CMO adapt to this & in fact then become a "Change Agent" within her company to make such a marketing transformation happen?
Scott Brinker had this wonderful insight:
"First, the core conundrum of accelerating change is this: advances in technology — marketing technology as subset of that — seem to grow in an exponential fashion (i.e., Moore’s Law), but the ability for individuals and organizations to absorb those new capabilities is limited by a much slower human adoption curve. The tension between these two dynamics is clearly going to be the organizational dilemma of the 21st century".
Technology changes exponentially; organizations change logarithmically.
It’s why the role of “change agent” may ultimately be the most important hat for marketers to wear.
CMO's will have an interesting time being the flag bearers of this change. Interestingly, they will have to hugely leverage technology to drive such a transformation.
Not everything that counts can be counted, not everything that can be counted counts.’ Einstein said this years ago & marketers lived with the philosophy as they rarely had the data. But in earlier days, advertising was all about creativity & possibly data did not have much of a place here!
But now data seems to be cutting a wider swathe & marketing seems to be in the midst of the “perfect storm” with digital, mobile & content coming together to create mountains of data.
Till recently, when we spoke about Data based marketing, it always seemed to be a niche with most marketers doing it as an “add on” to the big marketing jobs consisting of Advertising & promotions. Data based marketers seemed to be these very passionate people with comparatively little impact in the bigger scheme of things.
Also data seemed to be more important in some industries, banking & telecom as against others like FMCG! But it is interesting how this world is changing! And the changes are not only driving a larger “data orientation” amongst marketers, it is also driving a fundamental change on how Marketing can contribute to Revenue generation.
Harvard Business Review called “data scientist” the “sexiest” job of the 21st century, and McKinsey predicts a shortfall of about 140,000 by 2018. Yet most companies are still clueless as to how they’re going to meet this shortfall.
HBR has an interesting take: “Seismic shifts in both technology and consumer behaviour during the past decade have produced a granular, virtually infinite record of every action consumers take online. Add to that the oceans of data from DVRs and digital set-top boxes, retail checkout, credit card transactions, call centre logs, and myriad other sources, and you find that marketers now have access to a previously unimaginable trove of information about what consumers see and do”
In many ways, the new Internet based companies are changing the way “data” is perceived by mainstream marketers. It’s suddenly sexy to talk data, even if you are an advertising agency. Google built its $38 billion business selling ads based on data about how people search and browse the Web. Facebook uses what it knows about its one billion users to sell targeted ads. And there may be no better data than the information in Amazon’s 152 million customer accounts. Since last year, the world’s largest online retailer has been packaging information on what it knows about consumers so that marketers can use it to improve their marketing decisions. And of course Twitter is also actively trying to ally with advertising so that mass advertisers see it as complementary to TV!!
All of this is creating a new data based paradigm amongst marketers of all hues! Here are a few examples of a large “data shift”:
- How the world experiences TV has fundamentally changed. We no longer watch TV as a silent participant, rather as an active voice.Watching TV with a laptop, smart phone, or tablet in hand is becoming more visible in many households. At one level this is impacting viewership of TV & at the same time this is great news for advertisers and programmers looking to engage viewers. Last year, 32 million people in the U.S. tweeted about TV programming: big events, like the Super Bowl (24 million Tweets) or their favorite weekly series, like American Idol (5.8 million Tweets during 2012). People tweet so much about TV that Twitter is becoming a fundamental part of how TV is measured. Twitter has seen this shift & recently announced the availability of TV ad targeting on Twitter. TV ad targeting works by using video fingerprinting technology to automatically detect when and where a brand’s commercials are running on TV, without requiring that advertiser to do any manual tracking or upload media plan details.
2. Even as Twitter has grown into a media and marketing giant, not everyone is persuaded that the social media site is useful for selling things. The perception is that Twitter is useful for “top of the funnel” marketing — building brand awareness and so on — but that it has yet to deliver paying customers in the way that GoogleAdwords can. Now Twitter has responded with a new ad product. The product, called a “Lead Generation Card,” lets marketers post expanded tweets that invite users to sign up for stuff right inside Twitter:
3.The head of the research lab at the New York Times says the newspaper has launched an advertising product called Sparking Stories that allows advertisers to insert ads into specific content that is trending on Twitter.
The new “Sparking Stories” advertising product gives advertisers the ability to place their ads inside those specific stories. Said Zimbalist:
“We developed this tool that lets us see what stories are trending, so now we’ve created an API that lets our ad server talk to this tool, and we’ve created an ad product called Sparking Stories, where an advertiser can come in and buy a package of stories that are trending right now on Twitter, irrespective of section or context or topic — just the stories that are really breaking through right now on social media.”
Imagine what kind of consumer data is being produced as marketers ramp up advertising as described above. How marketers bring all this data together into an intelligent “Digital exchange” & how they do the analytics on it is going to be a large competitive advantage for companies. This is also going to keep getting Marketing & IT together into the same game!
While Big data is being continuously talked about, it is Open data that seems to be more revolutionary in nature. Open data is a movement where more & more data is being brought into the public space. Actors in the public, private, and development sectors are beginning to recognise the mutual benefits of creating and maintaining a “data commons” in which this information benefits society as a whole.
So is Personal data becoming a new economic “asset class”, a valuable resource for the 21st century that will touch all aspects of society. On an average day, users globally send around 47 billion (non-spam) emails and submit 95 million “tweets” on Twitter. Each month, users share about 30 billion pieces of content on Facebook. The impact of this “empowered individual” is just beginning to be felt. Here is a snippet from an interesting World Economic forum report:
The types, quantity and value of personal data being collected are vast: our profiles and demographic data from bank accounts to medical records to employment data. Our Web searches and sites visited, including our likes and dislikes and purchase histories. Our tweets, texts, emails, phone calls, photos and videos as well as the coordinates of our real-world locations. The list continues to grow. Firms collect and use this data to support individualised service-delivery business models that can be monetised. Governments employ personal data to provide critical public services more efficiently and effectively. Researchers accelerate the development of new drugs and treatment protocols. End users benefit from free, personalised consumer experiences such as Internet search, social networking or buying recommendations.
And that is just the beginning. Increasing the control that individuals have over the manner in which their personal data is collected, managed and shared will spur a host of new services and applications. As some put it, personal data will be the new “oil” – a valuable resource of the 21stcentury. It will emerge as a new asset class touching all aspects of society
Data is actively collected from individuals who provide it in traditional ways (by filling out forms, surveys, registrations and so on). They are also passively collected as a by-product of other activities (for example Web browsing, location information from phones and credit card purchases). The increasing use of machine-to-machine transactions, which do not involve human interaction, is generating significant amounts of data about individuals. All of this data is further analysed and mashed together to create inferred data.
In addition, individuals are no longer merely the subjects of data – they are also being recognized as “producers” of data. For example, digital personal-health devices such as Fitbit and Nike+ Fuelband measure daily physical activities. They provide a new way of capturing a rich data set about an individual. These devices present an opportunity to combine and commingle intimate,high-resolution, activity-based health data with other data sets to provide a daily health dashboard for individuals. It helps them set wellness targets, measure progress and more effectively engage in achieving healthier lifestyles
So how do you motivate consumers to share personal data in ways that are innovative? How do you begin to capture customer behaviour that allows you to market more effectively to consumers.
Can Marketers come up with innovative concepts that make it easy for consumers to share their personal data?
Here is a great example from the San Francisco-based StreetOwl. This interesting company has figured out a way to make data sharing a "win-win" for youngsters too. The company uses an age-old tactic: bribery.
Its RefuelMe iPhone app tracks driving behavior, earning points for proper speed, acceleration, braking and cornering (see below).
The app measures how teenagers drive, including factors such as speeding, accelerating, breaking or cornering. Then the app gives them rewards from their parents for safe driving. Parents meanwhile can view a web dashboard to see how their teens are driving. The company plans to make money by providing lead generation to insurance companies..
Young drivers earn awards established by their parents. In the example below, you can see that the driver is about 1% of their way to earning a $25 Chevron card
What does this mean for marketers?
- It would be interesting to ask that if given the appropriate checks and balances, would consumers like to be given the option to make some of their data public?And can this public data be used in anyway by others to make better goverment policy- Reducing mobile recharges in a district could alert the goverment about lower seasonal income.
- How can banks & financial institutions construct Reward & loyalty programs for younger consumers?
- This can also lead to interesting "community loyalty" concepts-eg:where a neighbourhood becomes "safer" by a collective change in behaviour.
- This has huge implications on further Customer Intelligence & data mining.
- And of course, this has many implications regarding data privacy& ethical issues of data sharing.Marketers will need to learn to deal with this reality.
In his new book, How to Create a Mind, technologist Ray Kurzweil estimates that a human brain can recognize 100,000 patterns. But consumers are producing a huge amount of information by the minute & our minds may just not be fast enough. “Big data” is what they call this data deluge & it has become the sexiest word in business in a very short time.
I wrote about this earlier & made the point that the current data situation for most companies is like having sections of a jigsaw puzzle in different rooms, but the puzzle keeps growing without a “puzzle master” integrating all this. The analyst, like the “ring master”, is really the “puzzle master” here & she needs to think very differently to do this. We don’t need more data; we need the correct interrelationships between data to be established & then we need “Big execution commitment” to make the data matter, by bringing decisions closer to the front end of every business.
You can read my earlier post here:Big data is puzzling
But clearly Big data is creating a discontinuity in the market place! Estimates suggest that more than a zettabyte (that’s a 1 followed by 21 zeroes) of information now circulates around the internet. Most minds will need help before they can analyse this massive stream of information, likened to drinking from a firehose! Darian Shirazi, founder of Radius Intelligence Inc., calls this a problem of "haystacks without needles." Companies too often "don't know what they're looking for, because they think big data will solve the problem," he says. So Analysts will have to treat "Big data" differently & overcome a set of issues before being able to leverage it.
And of course there is also a Dark side to "Big Data". Some of the initiatives out of Big data are downright scary:
1. If I keep my meeting schedule in a Google calendar & get an external feed of traffic conditions, shouldn’t my phone tell me when to leave for my next meeting? (Check! – get Google Now).
2. Progressive, a insurance company, is one example of a company using big data projects to transform their business. Using detailed information about customers' driving habits, the insurer has created a usage-based model that defines a policy's price down to the individual. Progressive gets the data through a device a driver plugs into a car's diagnostic port, according to its website. It can track how often customers slam on their brakes, drive late at night and other possibly risky driving habits. If the data shows a customer is driving safely, they can get significant discounts on their insurance.
Big data is so sexy & the hype of inflated expectations is so high that its about time we started seeing results. I am planning to look at Big data across a range of industries...here is the first one-Big data & the media world!
Media companies have such a huge treasure trove of data. Imagine if Times of India, Forbes or The Wall street Journal were to put together a “one view” of its readers & actually get to know the households that it delivers to each morning at a personal level. Some 80 percent of what can be considered Big data is unstructured or semi-structured information. This is where Media companies have masses of information & they can use their information to make more effective decisions in their business of journalism.
Kenneth Neil Cukier is the Data Editor of The Economist. He argues that having access to vast amounts of data will soon overwhelm our natural human tendency to look for correlation and causality where there is none. In the near future, we’ll be able to rely on much larger pools of “messy” data rather than small pools of “clean” data to get more accurate answers to our questions.
Cukier says something very interesting: “When we teach journalism in the future, we’re not just going to teach people the fundamentals of how to do an interview, or what a lede paragraph is. We’re going to tell people how to interview databases. And also, just as we train journalists by telling them that sometimes people that we interview are unfaithful and lie, we’re going to have to teach them to be suspicious of the data, because sometimes the data lies, too. You have to bring the same scrutiny as in the analog world — talking to people and observing — to the data as well.”
The Financial Times have been an interesting case study in the paywall debate & they are huge users of data. They've had their metered paywall approach for several years, but they are often regarded as an exception because of the specialist nature of the information they communicate. Estimates for Feb 2013 suggest: 286,000 print subscribers and 316,000 digital subscribers — the first newspaper to see digital surpass print. They are probably amongst a few Media companies that boast of a large analytically savvy team. The data team has about 30 people, organized into three groups: Data Analytics & Campaigns, Data Product Development, and Data Technology
The FT, by requiring sign-in to access even the free content, has had years to build up a massive database of users – and any free user is a potential subscriber. Using analytics to target the tipping point where people might begin to pay for the product is a smart move. Since enforcing on-site registration, the FT has gathered not only a vast amount of data about who its readers are and how to sell subscriptions and ads to them — the paper also knows a good deal about what they read and when, as well as the kinds of editorial products that appeal to them.
Read more about FT at Data led marketing at Financial Times
We know that channels can be used & abused! Telecalling has already reached that pinnacle in India. Email is already there with the amount of spam we get. Marketers need to be conscious of this & treat this medium responsibly. The biggest bane is that most marketers treat Email as a mass marketing medium. Email is not Mass marketing & the only way you can make it work is if you make it relevant & create a Relationship marketing paradigm!
I spoke about this at a conference a few days ago organised by the IAMAI. Nishad from Cequity was my co-creater for the presentation & you can access our presentation here: Email marketing: Used & Abused
The total number of worldwide email accounts is expected to increase from 3.3 billion accounts in 2012 to over 4.3 billion accounts by year-end 2016. This represents an average annual growth rate of 6% over the next four years. Nearly half of worldwide email users are in the Asia Pacific region.
Radicati Group, a technology market research firm, estimates that more than 2.8 million emails are sent every second and about 90 trillion emails are sent per year.(estimates vary by source ...but billions of mails for sure!)
Around 90% of these millions and trillions of message are but spam and viruses.
I spoke at the conferance about the need to relook at how we do Email marketing.
The 6 takeaways that I spoke about at the IAMAI conference
- Most used. Most abused: Email is hugely misused & we as marketers are responsible for using this medium responsibly. Marketers need to create a community effort to work on this malaise. I don’t see too many marketing associations taking this up. I do know that IAMAI is active in this space but more participation is definitely required.I am willing to join other marketers in this journey , so lets talk!
- Relationship Vs Mass Marketing: Email is not mass marketing period!Thinking 1to1 marketing needs a change in mindset.
- Desktop to Mobile: Large movement towards opening emails in mobile phones & marketers need to design emails for this & also think through how to change the "calls for action" given this reality. In 2013, India is supposed to get to a 45 million smart phone mark! (Nielsen estimate). That allows for a lot of creative thinking & email can integrate with this so beautifully.
- Integrated thinking: Email does not stand alone but needs to be part of a larger Integrated marketing plan. How many CMO's even spend time on this medium..or is it ignored & abused within the marketing fraternity!
- Email + Social: Make email work harder for you by integrating it with social. Commercial TV took 13 years to reach 50 million households; it took Facebook just a year to hit the 50 million user mark. It took Twitter 9 months to touch 50 million users. More than a billion people now log into Facebook everyday. To date, only two national states have breached this barrier: China and India.Mastering this new animal (Social) requires a different breed of people and process due to its real-time nature. Marketers need to marry real-time interactions with traditional marketing campaigns & analytics. Silos need to be broken so that marketers don’t think Brand, digital & campaign differently but rather run a “strategic thread” & integrate the customer engagement.
- Creating a “single source of truth”: Bring all of the data that we as marketers have into what I call a “digital hub” which allows marketing to have a “single source of truth”. And once you have this, improve your analytics by not looking only at Email open & click through rates but connect that data with Social data & to the CRM (actual buyer behaviour) that is with you.
Commercial TV took 13 years to reach 50 million households; it took Facebook just a year to hit the 50 million user mark. It took Twitter 9 months to touch 50 million users. More than a billion people now log into Facebook everyday. To date, only two national states have breached this barrier: China and India
The number of worldwide email accounts is projected to increase from over 2.9 billion in 2010, to over 3.8 billion by 2014. However, Social Networking currently represents the fastest growing communication technology among both consumers and business users which are projected to grow to over 3.6 billion accounts by 2014.
And yet Email marketing is far from dead!!
One of the reasons Email marketing is not going away too soon, is just that it is more profitable! According to a 2011 study by the Direct Marketing Association (DMA), e-mail marketing yields a return of $40.56 per dollar spent, compared with $22.24 for search, $12.71 for social networking and $10.51 for mobile. In fact, the DMA’s 2016 estimate pegs e-mail marketing’s ROI at $35.02 per dollar compared with social’s $13.43. (Source: article written by Vineet Manghani,Cognizant)
Unveiling the full potential of Social requires an “integrative” mindset. It demands marketers to think in a very 1 to 1 way across both mass & personalised media. And this requires marketing to create a “Campaign backbone” that leverages the rich data that consumers are producing as they wade through their “social life”.
Over the last few years,the Facebooks, Googles and Amazons of the world have leveraged “Big data” to create such a “campaign backbone” . This allows these companies to improve their decision-making based on the infrastructure technology and analytics-related software they have been developing & talk to consumers in a far more “real time” fashion.
Every year organizations collect more and more data on customer “touch points”. Technology advances are allowing for the storage and analysis of data that just 5 years ago wouldn’t have been possible
Companies need to look at Social & traditional email as a part of a “more integrated” data based Marketing strategy.
So how does this impact the good “old email” as a campaign?
In his book Permission Marketing, Seth Godin referred to email marketing as “the most personal advertising medium in history". That was 1999. Maybe we need to listen to that message to reinvent Email marketing.
In my view, that re invention is about how data can form a central part of how marketing campaigns are designed. And in that transformation how emails strategies can leverage a plethora of data-the humble “customer check ins” for something like Four Square being an example!
Social media check-ins provides marketers an unprecedented view into the lives of their customers and prospects. Knowing location, and understanding actual behaviours, creates opportunities to captivate an audience with greater relevance during moments when they are most receptive.
Here are a few examples of how Social instead of killing emails makes them a far more powerful medium:
- Use check-ins as triggers
Right timing a message always gets you far better response. The intent and the timing are clearly signalled by the check in. Check-ins also create opportunities to communicate with customers when they’re not in your store, but nearby, which is a great time to send a special offer.
- Improve segmentation with behavioural data
Check-ins is a window into your customers’ lives, enabling a deeper understanding of where they go and what they do. By analysing check-in data you can categorise & segment customers based on who shops at department stores & who is a high end fashion consumer.. But this requires marketers to create a “big data” environment which can process & analyse this data at speed
- Extend the definition of check-in
Typically, check-ins are an explicit act of using a location-based application to identify where you are. The term "soft check-in," which is an "implied" check-in from social media such as Twitter and Facebook, is now emerging.
For example, if someone tweets they just finished eating a "Mc Burger", it’s a pretty good assumption they are dining at the fast food chain. And, of course, there are the more obvious Facebook or Twitter posts such as "Standing in line to see Sky Fall", the popular James Bond movie !
Using a natural language filtering algorithm that extracts presence extends the number of check-ins marketers can exploit to engage with people and acquire customer information.
So to summarize:
- Mastering this new animal (Social) requires a different breed of people and process due to its real-time nature. Marketers need to marry real-time interactions with traditional marketing campaigns & analytics. Silos need to be broken so that marketers don’t think Brand, digital & campaign differently but rather run a “strategic thread” & integrate the customer engagement.
- Email needs to leverage customer intelligence & drive highly relevant communications to customers. Big data allows you to do that at scale & speed.
- Email needs to be integrated with Social & a larger brand strategy to maximise impact